Title :

Learning Boundary Edges for 3D-Mesh Segmentation

Author(s) :

Benhabiles, Halim [Auteur]
Geometry Processing and Constrained Optimization [M2DisCo]
FOX MIIRE [LIFL]
Lavoué, Guillaume [Auteur]
Geometry Processing and Constrained Optimization [M2DisCo]
Vandeborre, Jean Philippe [Auteur correspondant]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
Daoudi, Mohamed [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1

Journal title :

Computer Graphics Forum

Pages :

2170-2182

Publisher :

Wiley

Publication date :

2011-12

ISSN :

0167-7055

English keyword(s) :

3D-mesh
segmentation
learning
boundary edges
evaluation
ground-truth

HAL domain(s) :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Multimédia [cs.MM]

English abstract : [en]

This paper presents a 3D-mesh segmentation algorithm based on a learning approach. A large database of manually segmented 3D-meshes is used to learn a boundary edge function. The function is learned using a classifier which ...
Show more >This paper presents a 3D-mesh segmentation algorithm based on a learning approach. A large database of manually segmented 3D-meshes is used to learn a boundary edge function. The function is learned using a classifier which automatically selects from a pool of geometric features the most relevant ones to detect candidate boundary edges. We propose a processing pipeline that produces smooth closed boundaries using this edge function. This pipeline successively selects a set of candidate boundary contours, closes them and optimizes them using a snake movement. Our algorithm was evaluated quantitatively using two different segmentation benchmarks and was shown to outperform most recent algorithms from the state-of-the-art.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL